Google’s search for the perfect learning machine

Google’s quest to build the ultimate machine-learning system has produced some lessons of its own.

The project, code-named “Seti” in a nod to the search for life in outer space, is being used on huge data sets in an attempt to solve what Google calls “hard prediction problems.” Google revealed the name of the project in a blog post that also acknowledged the limits of engineering.

Machine learning is a favorite topic of Google co-founders Sergey Brin and Larry Page, and is useful for improving translation algorithms and semantic understanding, according to Google. But, of course, it’s an enormously complex notion, one that can intimidate even Google’s computer scientists that could make use of such a system.

“We saw very early on that, despite its many significant benefits, machine learning typically adds complexity, opacity, and unpredictability to a system. In reality, simpler techniques are sometimes good enough for the task at hand,” Simon Tong wrote.



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